Research on multi-objective flow shop scheduling problem based on improved NSGA-III algorithm

Under the background of intelligence, this paper studies the actual workshop scheduling problem of the impeller company. From the perspective of reducing carbon emissions, combining the makespan and total operating cost of the machine as optimization indexes, a multi-objective mathematical model is established. Meanwhile, an improved NSGA-III algorithm was designed to solve the model. Compared with the experimental results of the genetic simulated annealing algorithm, better results were obtained in the three aspects of minimizing carbon emissions, minimizing total operating cost, and shortest completion time, to obtain the optimal scheduling scheme.